Introduction

The importance of asset performance in industrial operations cannot be overstated. Optimal asset performance is not only crucial for efficiency and productivity but also for overall profitability. Organizations that focus on enhancing asset performance gain a competitive edge by streamlining operations, reducing the risk of failures, and avoiding costly repairs. In this article, we will explore the significance of asset performance in industrial operations and the strategies organizations can employ to improve it. We will discuss real-world examples of successful asset management transformations and the role of technologies like Makini's universal API in real-time data retrieval. By implementing these strategies, organizations can enhance their operational excellence and achieve better asset performance.

In the realm of industrial operations, the integration of systems and the utilization of real-time data play a pivotal role in driving operational excellence. The ability to access instantaneous and detailed insights into asset performance enables organizations to make prompt decisions and take proactive measures. Makini's universal API serves as a powerful tool in this process, allowing organizations to extract real-time data from various systems and gain a comprehensive view of asset performance. By strategically monitoring key performance indicators (KPIs) and leveraging technologies like Makini's universal API, organizations can enhance their asset performance, improve efficiency, and drive overall operational excellence. In this article, we will explore the transformative potential of real-time data retrieval and integration in aftermarket processes, inventory management, and asset tracking. We will also delve into the future trends in industrial integration and how organizations can embrace emerging technologies to achieve optimal operational excellence.

1. Understanding the Importance of Asset Performance in Industrial Operations

The significance of optimal asset performance in industrial operations is paramount. It's the driving force behind an organization's efficiency, productivity, and ultimately, its profitability. It's not just a component of the operational machinery but the engine that powers seamless operations, reduces the risk of unexpected failures, and avoids costly repairs. By focusing on enhancing asset performance, organizations can significantly boost their operational excellence, creating a unique competitive edge.

Consider the case of UtilityCo, a North American transmission and distribution utility. The company adopted advanced analytics in asset management, leading to a transformative effect on their operations and financial outcomes. This strategic move led to a reduction of 20 to 25 percent in operating expenses and a staggering 40 to 60 percent in capital expenditures. This achievement is especially impressive given the various constraints such as affordability, inflation, supply chain bottlenecks, and the urgent need for investments in the energy transition.

UtilityCo's asset management transformation wasn't a random success; it was the outcome of a carefully designed roadmap. This plan aimed to expand the risk-based approach of asset management to two-thirds of their capital portfolio within two years. The use of advanced analytics enabled the optimization of capital expenditures, reduction of preventive and corrective maintenance operating costs, and replacement of the riskiest assets, leading to enhanced reliability.

UtilityCo's approach wasn't solely based on numbers and algorithms; it also involved a significant shift in their business operations. The company integrated the advanced analytics solution for asset management as part of a broader business transformation. This involved creating new technical roles such as data scientists and engineers, upgrading IT infrastructure, and setting up a digital center of excellence to manage these new functions.

There were challenges in UtilityCo's journey, including a lack of a risk-based approach and decentralized asset management operations. However, these hurdles were tackled effectively through the implementation of advanced analytics. The lessons learned, such as the importance of data quality, talent and capabilities, change management, and governance, were invaluable.

UtilityCo's experience underscores the potential of focusing on asset performance improvement. It serves as an inspiration for other organizations aiming to boost their operational excellence and secure a competitive advantage. By employing advanced analytics and implementing strategic alterations, businesses can redefine their maintenance processes, unlock significant savings, and enhance the reliability and performance of their networks. This is the future of asset performance in industrial operations, a future brimming with potential and promise.

To achieve such outcomes, organizations can consider several approaches.

One way is to implement preventive maintenance strategies that involve regular inspections and maintenance tasks to identify and address potential issues before they escalate. Investing in condition monitoring technologies such as sensors and monitoring systems can provide real-time data on asset performance, enabling proactive maintenance actions. Furthermore, optimizing asset utilization through improved planning and scheduling can contribute to cost-effective asset performance improvement. Lastly, leveraging data analytics and predictive maintenance algorithms can help identify patterns and trends in asset performance data, allowing for more targeted and efficient maintenance interventions.

A proactive approach to asset management for better performance requires a comprehensive system that allows for real-time tracking and monitoring of assets. This can be achieved through the use of advanced technologies such as Internet of Things (IoT) sensors which provide valuable data on asset utilization, condition, and maintenance needs. By leveraging this data, organizations can identify potential issues before they occur, enabling them to take proactive measures to optimize asset performance and minimize downtime. Implementing predictive analytics and machine learning algorithms can further enhance asset management by enabling organizations to forecast asset performance and make data-driven decisions for maintenance and replacement.

It's also important to measure and track key performance indicators (KPIs) for assets. This can be achieved through the use of asset management software or tools that are specifically designed to monitor and analyze asset performance. These tools collect data such as asset utilization, maintenance history, downtime, and overall asset health. Tracking these KPIs provides valuable insights into the performance of assets and supports data-driven decisions to optimize asset utilization and improve overall operational efficiency.

Investing in asset performance improvement can offer several benefits for organizations.

It can enhance operational efficiency, reduce downtime, and improve overall productivity, leading to cost savings, increased revenue, and improved customer satisfaction. Asset performance improvement can help organizations identify and address potential issues before they escalate into major problems, minimizing the risk of costly breakdowns or failures. In the long run, investing in asset performance improvement can contribute to the long-term success and sustainability of organizations.

2. Strategies to Improve Asset Performance and Efficiency

Boosting asset performance and efficiency calls for a well-considered strategy that includes regular maintenance, predictive analytics, and the integration of cutting-edge technology for real-time monitoring. Regular maintenance ensures assets are kept in their prime condition, thereby reducing the chance of sudden failures. Predictive analytics, meanwhile, serves as a tool for identifying potential issues before they develop into significant problems, allowing for proactive maintenance.

A real-world example of this strategy is seen in the operations of Seattle Public Utilities (SPU). SPU, a public utility agency in Seattle, Washington, provides water, sewer, and drainage services to 1.3 million residents in King County. With a sewer system with a median age of over 80 years, SPU shifted from a reactive approach to a proactive stance in their pipe inspection and rehabilitation efforts. They adopted a strategy that involved pipe inspection, condition evaluation, risk assessment, capital investment, and implementation planning. By focusing on service equity, efficiency, and adaptive management, SPU successfully secured funding for a long-term rehabilitation plan for their aging sewer system.

To aid in this, SPU integrated innovative asset management software, which allowed them to develop a proactive rehab program and improve their understanding of system risk. The software's risk matrix feature was crucial in prioritizing pipe repair and replacement, enabling the team to concentrate on assets within a five-year rehab window. The software also integrated with other programs used by SPU, allowing them to pull data from different systems and evaluate risk within their system. This strategic and proactive approach led to a higher percentage of inspections completed, and SPU was able to develop a 40-year rehabilitation schedule, secure funding for rehab efforts, and transition from a reactive to a proactive position.

Alongside this, the utilization of state-of-the-art technology, such as Makini's universal API, can provide real-time data on asset performance. This access to data allows for swift decision-making and timely interventions. An example of such technology is the Prism platform by Building Engines, used to maximize net operating income. The platform offers various features, including Prism Mobile, which provides engineers and tenants with an exceptional mobile experience. It also offers Prism Reporting to deliver insights into the health and performance of buildings.

One case study that underlines the effectiveness of such technology is the implementation of Hank, an AI-powered tool on the Prism platform, by Royal London Asset Management. The implementation led to considerable improvements in HVAC operations and energy efficiency in a 125,000 square foot property, resulting in a 21% total energy savings and a 708% return on investment.

In essence, the strategic implementation of measures such as regular maintenance, predictive analytics, and the use of advanced technology can significantly enhance asset performance and efficiency. This approach not only lowers the risk of unexpected breakdowns but also enables organizations to be proactive in their maintenance efforts, leading to improved operational efficiency and cost-effectiveness.

3. Reducing Unplanned Equipment Downtime: Best Practices

Unplanned equipment downtime is a significant obstacle to productivity and efficient resource use. The implementation of a robust preventive maintenance program, predictive analytics, and efficient inventory management are critical strategies to combat this issue. Regular inspections, timely repairs, and proactive component replacement are fundamental elements of a successful preventive maintenance program, which can dramatically reduce downtime, extend equipment life, and enhance overall operational efficiency.

Take, for example, Delaware North, a top-tier food and hospitality company. They chose to migrate their enterprise applications and operations to Amazon Web Services (AWS) to reduce expenses and improve efficiency. Their transition led to a striking 90% reduction in their server footprint, which is projected to save the firm an estimated $35 million in IT acquisitions and maintenance over the next five years. They also utilized AWS's security best practices, streamlining compliance tasks and improving security and disaster recovery capabilities.

Another effective strategy is the integration of systems like Makini's universal API, which provides real-time data on equipment status. This allows for immediate action to prevent or mitigate downtime. Mu Sigma, a firm specializing in big data analytics and decision sciences, has demonstrated the benefits of this approach. They developed a customer segmentation model based on spending values and engagement levels, along with a predictive model to calculate customers' likelihood of fitting into different spending categories. This resulted in a 10% improvement in customer targeting, $20 million in additional revenue, and $10 million in cost savings for a casino operator client.

A preventive maintenance program can be further enhanced by implementing a scheduled maintenance checklist, performing regular equipment audits, and using condition monitoring techniques to identify potential issues before they escalate into significant problems. Also, the use of computerized maintenance management systems (CMMS) can streamline maintenance processes and track maintenance history, enabling better decision-making. By adopting these strategies, organizations can significantly reduce unplanned equipment downtime, leading to substantial cost savings and improved operational efficiency.

4. Maximizing Inventory Optimization through Effective Integration

Integrating maintenance and inventory systems can significantly enhance inventory management efficiency. This integration ensures timely access to necessary components, reducing operational downtime and boosting asset productivity. Makini's universal API is an excellent tool for facilitating this integration. Real-time data on inventory levels, made accessible through this integration, supports a more effective approach to inventory management.

In the modern omnichannel retail environment, efficient order management is crucial for meeting customer demands across all platforms. To remain competitive, suppliers need to optimize their order management processes. The necessity for proficient inventory management is further highlighted by factors such as globalization, elongated supply chains, and market influences.

Inventory often constitutes a significant portion of a supplier's capital. With extended supply chains and the increasing cost of raw materials, inventory is under more pressure. To optimize these processes, implementing inventory management software like Fishbowl, NetSuite, or SAP Business One is recommended.

Reviewing your Electronic Data Interchange (EDI) solution is essential to ensure maximum efficiency and vital functionalities. The integration of inventory management, EDI, and back-office systems leads to resource conservation, time-saving, and reduced errors.

The level of automation in your order management system should be tailored to your business needs. Striking a balance between full automation and manual review is vital to achieve both speed and accuracy in the order management process.

The scalability and flexibility are essential features to consider when choosing a provider, to accommodate future software updates and growth. A centralized interface can provide real-time access to order management data, promoting agile responses. Custom fields can be designed to cater to unique business needs. A provider with experience and a customer service-centric approach is a critical element for successful order management integration.

The advantages of optimizing the order management process are numerous. These include real-time inventory visibility, improved e-commerce and drop-ship capabilities, enhanced response time to issues, centralized view and control, enhanced relationships with retail partners, reduced labor costs, and the ability to achieve turn rate and ROI goals.

For e-commerce companies, inventory management is critical for maximizing sales and improving customer satisfaction. Accurate product availability status, immediate delivery, and store pickup are key factors in customer retention and sales.

A six-step process is proposed for evaluating inventory systems and developing an improvement action plan. This process includes assembling a team, assessing objectives, collecting metrics, documenting inventory processes, integrating with all inventory-related systems, and developing an action plan. Metrics such as order fill rates and inventory accuracy are vital for assessing inventory management.

Common problems in inventory management include inaccurate delivery dates, inventory inaccuracy, and failure to assign items to customer orders. Creating flow diagrams and documentation of current inventory processes can help identify potential problems and timing differences. The integration of all inventory-related systems is important for creating a single version of the truth. Developing an action plan involves prioritizing changes and estimating effort and benefits. Improved inventory management is critical for improving sales and the customer experience in e-commerce companies.

When integrating Makini with asset management systems, it's essential to follow several best practices for a smooth and efficient integration process. These best practices include defining clear integration goals, selecting the right integration method, ensuring data compatibility, implementing data validation and error handling, and testing and monitoring the integration. Following these best practices can help organizations successfully integrate Makini with their asset management systems, enabling streamlined and efficient asset management processes.

Makini's Universal API platform offers integrations and use cases for various purposes. Although there's no specific mention of case studies on improving asset performance with Makini's Universal API, it's plausible that such case studies exist. Organizations might have used Makini's Universal API to enhance their asset performance through integration and optimization.

5. The Role of Real-Time Data Retrieval in Operational Excellence

Real-time data retrieval plays a pivotal role in bolstering operational excellence. It delivers rapid and detailed insights into asset performance, thereby facilitating prompt decision-making and proactive measures. Makini's universal API serves as a key tool in this process, enabling instantaneous data extraction from a multitude of systems and offering a comprehensive understanding of asset performance. This all-encompassing view equips organizations with the ability to make data-driven decisions that boost asset performance.

Real-time data retrieval not only enhances asset management but also extends its utility to various domains such as human resources, finance, healthcare, and information technology. For instance, it provides valuable insights into various aspects of human resources like employee benefits, performance reviews, recruitment, and workforce management. Similarly, in the information technology sector, it assists in managing data infrastructure, security, software development, and storage.

Makini's universal API is versatile and isn't confined to a specific industry. It finds application across a spectrum of sectors including aerospace, defense, automotive, healthcare, manufacturing, and retail, among others. This wide-ranging applicability enables organizations from various industries to tap into the potential of real-time data, consequently enhancing their operational efficiency.

In the realm of industrial maintenance and asset management, real-time data retrieval brings manifold benefits. It offers immediate access to the latest information about assets, thereby enabling timely decision-making and proactive maintenance strategies. With real-time data, maintenance teams can monitor asset performance in real-time, detect anomalies or potential failures early, and initiate preventive actions to circumvent expensive breakdowns. Moreover, real-time data retrieval paves the way for predictive analytics and machine learning algorithms to identify patterns and trends, leading to better asset performance optimization and resource allocation.

Makini is a platform that offers integrations with diverse systems, including Computerized Maintenance Management System (CMMS) and Enterprise Asset Management (EAM) systems. It enables real-time data retrieval and integration with these systems. By leveraging Makini, businesses can effortlessly link their CMMS and EAM systems with other data sources, thereby accessing the latest information and streamlining their maintenance and asset management processes.

Makini.io provides a universal API for real-time data retrieval. The advantages of utilizing Makini's universal API are manifold. It seamlessly integrates with a variety of systems, such as Oracle Fusion Cloud Warehouse Management and K-Motion Warehouse Advantage, enabling users to extract real-time data from these systems and access it through Makini's API. The API has been designed to offer a simplified and standardized way of accessing and retrieving data, thereby making it simpler for developers to work with and integrate into their applications. By leveraging Makini's universal API, users can conserve time and effort by eliminating the need to develop custom integrations for each individual system.

In a nutshell, the incorporation of real-time data retrieval is crucial in driving operational excellence across various industries. It provides timely and valuable insights into different operational aspects, thereby enabling swift and informed decision-making. With tools like Makini's universal API, organizations can utilize this real-time data to enhance their overall performance.

6. Revolutionizing Aftermarket Processes: Key Techniques for Success

In the realm of aftermarket operations, which includes maintenance and repair services, the fusion of systems and the use of real-time data can bring about a significant transformation. This not only elevates the quality of services but also heightens customer satisfaction, ultimately leading to a boost in revenue.

To illustrate this point, let's look at the case of Chiquita, a leading name in the banana commodity sector. This company, in its quest for expansion in a mature market with limited growth potential, aligned with a firm that had developed an innovative packaging technology to address the challenges in banana distribution. This technology enabled bananas to be shipped at regular refrigerated or ambient temperatures, widening their distribution potential significantly.

With the guidance of Valen, a firm specializing in growth and innovation strategies, Chiquita realized that the prime use of this technology was not cost reduction. Instead, it presented an opportunity for extended distribution. This insight led to the unique vision of selling bananas wherever Snickers bars were sold, marking a shift in the distribution pattern.

This innovative approach was put to the test with the launch of the 'Chiquita To Go' model at Starbucks, where a single banana was sold for a premium price of $0.75. The success of this initiative led to the expansion of the distribution channel into Europe. This venture was successful enough to cultivate a growth beachhead for Chiquita, allowing the company to sell other fruit products to Starbucks, convenience stores, and other outlets.

In a similar fashion, the retail company Wawa employed the Blue Ocean Strategy to redefine industry boundaries, leading to low costs and high profits. Despite the challenges posed by the 2008 financial crisis and competition from other companies, Wawa managed to transform from an iron foundry to a convenience store, becoming the 34th largest private company in the US with millions of customers and billions in sales.

Likewise, aftermarket processes can also be transformed through system integration and real-time data retrieval. For instance, consider the Makini's universal API, which allows for the seamless integration of these processes with other systems. This integration provides real-time data that can be used for constant improvement, resulting in enhanced service quality and customer satisfaction.

The successful integration of Makini's API with a data management platform, such as Oracle Fusion Cloud, can provide organizations with up-to-date information to effectively manage their maintenance and repair operations. Additionally, this integration with Makini's platform can optimize operations, reduce errors, and provide a seamless experience for customers.

The integration of the Makini API in aftermarket services offers numerous benefits for businesses. It allows them to connect their aftermarket services to the Makini platform, enabling them to access real-time data, automate processes, and provide seamless experiences for their customers. This integration can enable businesses to efficiently manage inventory, track orders, and provide timely updates to customers, ultimately leading to improved service quality and increased customer loyalty.

However, integrating the Makini API in maintenance and repair services requires adherence to best practices to ensure seamless communication and efficient data exchange. These include understanding the API documentation, implementing secure authentication mechanisms, handling error messages, validating and sanitizing all input data, adhering to rate limits set by the Makini API, implementing logging and monitoring mechanisms, keeping track of the Makini API version, and thoroughly testing the integration to ensure all functionalities work as expected.

Moreover, Makini's API can also be implemented for real-time data retrieval in aftermarket processes using specific code snippets. However, these code snippets may need to be adjusted based on specific implementation requirements.

In summary, the success stories of Chiquita and Wawa serve as proof of the potential for transformation within industries through effective integration and real-time data retrieval. The application of these methods can revolutionize aftermarket operations, resulting in improved service quality, increased customer satisfaction, and an overall boost in revenue.

7. Tracking Asset KPIs: A Strategic Approach to Enhance Performance

Monitoring Key Performance Indicators (KPIs) strategically can be a powerful tool in enhancing asset performance. The measurable values of these KPIs enable organizations to assess their asset performance, identify areas requiring improvement, and track their growth over time. This approach's effectiveness is exemplified in the small residential community of Warfield, British Columbia, which has made significant advancements in their asset management efforts.

In 2017, Warfield formally incorporated asset management into its operations, aiming to bolster its asset data and information using funds from the Municipal Asset Management Program (MAMP). The village's strategic choice to digitize and map all its linear assets, including roads and water and sanitary systems, by employing open-source geographic information systems software, has emerged as a cost-effective solution. This innovative strategy has not only bridged data gaps but also laid the foundation for more efficient operations and informed decision-making.

An integral part of Warfield's success has been the engagement of external technical support, proving more cost-effective than employing full-time staff. These consultants have played a crucial role in establishing the digital asset register and continue to maintain and update it. This partnership has led to an enhanced "state of infrastructure" report that lists all assets and estimates replacement costs, thus offering a detailed and comprehensive overview of the village's assets.

Additionally, Warfield's staff has received training to effectively utilize the asset management system, further augmenting their decision-making abilities. The village's progress in asset management is now quantifiable, facilitating easier access to infrastructure funding.

Warfield's journey of continuous improvement in asset management is a collaborative one. They have proactively engaged with neighboring municipalities to exchange knowledge and address infrastructure challenges, thereby creating a network of peer learning.

As Warfield looks to the future, they plan to identify critical assets, devise a long-term financial plan for asset replacement, and evaluate risks to key infrastructure assets. Their journey underscores the power of strategic tracking of asset KPIs and the significant enhancements it can bring about in operational efficiencies.

In line with these efforts, technologies such as Makini's universal API can facilitate real-time tracking of asset KPIs. This technology can offer valuable insights, contributing to the ongoing endeavor to enhance asset performance. Therefore, it is through the integration of strategic tracking and technological facilitation that organizations can truly elevate their asset performance management.

8. Embracing Future Trends in Industrial Integration for Operational Excellence

As we venture into the future, the industrial landscape stands on the brink of a transformation, with cutting-edge technologies like IoT, AI, and machine learning at the forefront. These technologies promise to redefine operational excellence, providing real-time insights, predictive analytics, and automated decision-making capabilities to enhance asset performance and efficiency.

A key development in this transformation is the shift towards IT/OT convergence in critical infrastructure and industrial firms. This change is fueled by the need to embrace innovative technology and new business models, a failure to do so could risk their market standing.

The merging of IT and operations teams has been crucial in achieving digital transformation and enhancing operational efficiency. IT teams now aid operations in real-time decision-making through edge computing, providing quick access to critical data and promoting enterprise-wide data sharing.

There's also a noticeable shift in maintenance strategies. Traditional preventive maintenance schedules are being replaced by predictive maintenance technologies. These technologies utilize real-time data collection and analysis to predict equipment failures and schedule repairs during planned downtime, thereby minimizing unexpected operational disruptions.

Additionally, the use of wireless technology is becoming increasingly viable and cost-effective in industrial settings. It offers flexibility, adaptability, and substantial cost savings. However, the interconnectedness fostered by these advancements also brings about critical cybersecurity concerns. This calls for a cooperative approach between IT and operations to establish robust security measures that protect the organization from threats while avoiding downtime.

Companies like Resolute Mining Ltd and Nissan Motor Corporation serve as successful examples of these strategies. Resolute Mining Ltd employs real-time analytics for remote mining operations, enhancing infrastructure redundancy and network availability, thus reducing downtime. Nissan, on the other hand, has streamlined operations and prevented breakdowns with a secure, high-speed IoT network at their Tochigi plant. This network utilizes big data analytics to identify maintenance procedures that can prevent equipment failures, thereby enhancing manufacturing efficiency.

Likewise, Bangalore International Airport (BIAL) has boosted its operations by implementing automation and data-driven decision-making. They use cutting-edge technologies to track and monitor airside operations, improving communication and operational efficiency. CKW AG, central Switzerland's largest energy service provider, underwent a network transformation to ensure reliable and secure operation of its power distribution network, thereby enhancing its cybersecurity standards.

The integration of advanced technologies like IoT, AI, and machine learning into industrial operations is more than just a trend; it's a necessity for future success. This integration, coupled with the convergence of IT and OT, predictive maintenance, and improved cybersecurity measures, can significantly enhance operational excellence. The key is to remain flexible and adaptable, much like the Makini's universal API.

Makini's API offers integrations with various platforms and allows for seamless integration with these emerging technologies. To perform predictive analytics with the Makini API, data retrieved from the API can be analyzed using appropriate algorithms and models to generate predictions and insights that can drive decision-making and improve business outcomes. When integrating the Makini API with emerging technologies, it's important to ensure that the API is properly documented with clear instructions on its use. It's also crucial to follow industry-standard security practices, thoroughly test the integration before deployment, and stay updated with the latest developments and enhancements in the Makini API

Conclusion

The importance of asset performance in industrial operations cannot be overstated. Optimal asset performance is crucial for efficiency, productivity, and overall profitability. Organizations that focus on enhancing asset performance gain a competitive edge by streamlining operations, reducing the risk of failures, and avoiding costly repairs. Real-world examples, such as UtilityCo's asset management transformation and Chiquita's innovative distribution strategy, demonstrate the transformative potential of strategic approaches to asset performance improvement. By leveraging technologies like Makini's universal API for real-time data retrieval and integration, organizations can enhance their operational excellence and achieve better asset performance.

The significance of real-time data retrieval in driving operational excellence cannot be ignored. Access to instantaneous and detailed insights into asset performance enables organizations to make prompt decisions and take proactive measures. Makini's universal API serves as a powerful tool in this process, allowing organizations to extract real-time data from various systems and gain a comprehensive view of asset performance. The integration of systems and the utilization of real-time data have proven successful in various industries, from water utilities like SPU to retail companies like Wawa. By monitoring key performance indicators (KPIs) and leveraging technologies like Makini's universal API, organizations can enhance their asset performance, improve efficiency, and drive overall operational excellence.

To achieve optimal operational excellence and maximize asset performance, organizations should embrace emerging technologies like Makini's universal API. This powerful tool enables real-time data retrieval and integration from various systems, providing valuable insights for decision-making and proactive maintenance strategies. By implementing preventive maintenance strategies, optimizing asset utilization through improved planning and scheduling, leveraging predictive analytics algorithms, and closely tracking KPIs for assets, organizations can unlock significant cost savings, reduce downtime, improve productivity, and ultimately achieve long-term success. To learn how Makini’s Universal API can help you build 100+ product integrations with ease by scheduling a demo with one of our integration experts click here